Dynamic groups in histogram
This demo shows a histogram where the bins dynamically adjust based on the selected filter context, making it suitable for scenarios with multiple slicers. The underlying data comes from a subset of the Superstore dataset. The histogram displays the number of products sold across five price ranges (also known as bins). These bins are calculated by taking the difference between the minimum and maximum sale prices in the current filter context and dividing that range into five equal intervals. From this, the lower and upper boundaries of each bin are derived. An additional technique is used to ensure the bins automatically update whenever the filter context changes. For example, if the minimum sale price shifts from $50 to $60 and the maximum changes from $200 to $250, all five bins are recalculated so that they now start at $60 and end at $250, rather than using the original range. Because there is no native way to display dynamic bins directly on a bar chart, the bin ranges are shown using calculated text fields overlaid on the x-axis.Raise the Bar | QuickViz | Top10 Luxury Brands ♣
This striking chart, framed elegantly, presents the Top 10 Luxury Brands ranked by their Market Value (in Billions of Dollars), highlighting their respective values and countries of origin for a competitive overview. eyJrIjoiOWQwODU1MzktMWYyZi00NjBkLTljZTQtYjdkM2YxOGY0MDIyIiwidCI6ImY0Yzk2Mjg0LTA5M2QtNDgwOS1iZTNkLTg3ZDY3ZGY3MDkxYyJ9&embedImagePlaceholder=true
🎓 The College Quest: Student Success and Admission Insights
This Power BI report explores academic insights from The College Quest in Fabricland dataset. The analysis highlights faculty excellence, program popularity, student satisfaction, and salary outcomes. Page 1 focuses on College Performance (affordability, happiness, experience), while Page 2 showcases Program-level Insights such as admission difficulty, alumni satisfaction, and scholarships. Built with clean visuals, consistent color theming, and dynamic DAX measures, this project demonstrates the balance between storytelling and analytics — turning raw data into actionable insights. eyJrIjoiMDU3N2JjZTEtOGNlZC00NWZkLWI4NzEtZmZmNDI1MTM4MmViIiwidCI6ImMyY2E1ZGZkLTI3YjgtNGIxOS05ZmJhLTc2OWJmYTBkNjY2NyJ9&embedImagePlaceholder=trueEvolution of Endangered Animal Species: IUCN Red List Data 2000 – 2025
This interactive Power BI report is based on data from the International Union for Conservation of Nature's Red List of Threatened Species, version 2025-2. It visualizes how the number of animal species classified as Critically Endangered, Endangered, and Vulnerable has changed between 2000 and 2025. The dataset covers five major animal groups (mammals, birds, reptiles, amphibians, and fishes) and represents global species assessments conducted by IUCN. Users can explore the trends over time through the timeline play axis, which animates yearly changes in species counts. Hovering over any animal category displays a tooltip with a line chart, showing the historical evolution of that category across all three conservation statuses, providing additional temporal context.Rise of Youtube Gaints (2015-2025)
“Rise of YouTube Giants (2015–2025)” explores how major YouTube creators and channels grew over a decade. The report highlights trends in subscriber growth, content categories, viewer engagement, revenue patterns, and platform shifts. It analyzes year-by-year performance, identifies breakout creators, compares global vs. regional influencers, and visualizes major milestones that shaped YouTube’s creator ecosystem.
